RANSAC - Wikipedia, the free encyclopedia: "RANSAC is an abbreviation for "RANdom SAmple Consensus". It is an iterative method to estimate parameters of a mathematical model from a set of observed data which contains outliers. It is a non-deterministic algorithm in the sense that it produces a reasonable result only with a certain probability, with this probability increasing as more iterations are allowed. The algorithm was first published by Fischler and Bolles at SRI International in 1981."

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SAX - jmotif - Walk through steps of Symbolic Aggregate approXimation. - A temporal data-mining toolkit based on SAX and TFIDF statistics. - Google Project Hosting: "SAX transforms a time-series X of length n into the string of arbitrary length , where typically, using an alphabet A of size a > 2. The SAX algorithm consist of two steps: during the first step it transforms the original time-series into a PAA representation and this intermediate representation gets converted into a string during the second step. Use of PAA at the first step brings the advantage of a simple and efficient dimensionality reduction while providing the important lower bounding property as shown in the previous section. The second step, actual conversion of PAA coefficients into letters, is also computationally efficient and the contractive property of symbolic distance was proven by Lin et al."

GNU Emacs Calc Manual: "To make a long story short, Emacs Lisp turned out to be a distressingly solid implementation of Lisp, and the humble task of calculating turned out to be more open-ended than one might have expected."

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